The rapidly growing Unmanned Aerial Systems (UAS) vehicle category with applications across a wide variety of configurations and mission profiles is introducing challenges in ensuring that applicable noise certification regulations are met. A framework is proposed for assessing regulatory compliance to noise standards, and for analyzing process effectiveness as well as outcomes of noise testing campaigns for Unmanned Aerial Systems (UAS). The objective of this capability is to drive improvements at the process level of noise certification through exploration and evaluation of alternative noise testing technologies and procedures. This framework is enabled by a Model-based systems Engineering (MBSE) workflow for creating verification models that represent requirements derived by applicable regulations under the CFR Part 36 noise certification (appendices J, H). As a digital thread-enabled approach, this environment allows for tracking and assessing adherence to noise regulatory practices through mapping noise data flows from test campaigns to metrics of interest as part of verification of meeting regulatory noise requirements. The assessment of improvement strategies and selection of testing procedures is demonstrated through case studies performed by small multi- rotor vehicles and operated for package delivery missions.
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